key: cord-1005118-56rt4wga authors: Pattnaik, Debidutta; Hassan, Mohammad Kabir; Kumar, Satish; Paul, Justin title: Trade credit research before and after the global financial crisis of 2008 – A bibliometric overview date: 2020-06-30 journal: Research in international business and finance DOI: 10.1016/j.ribaf.2020.101287 sha: 2edf0c87129cc8deee28869b6abaf557ce3aca66 doc_id: 1005118 cord_uid: 56rt4wga Abstract This study presents an overview of the state-of-the-art in trade credit research by examining 1191 publications between 1955 and 2019. Applying bibliometric and econometric tools, this study presents a comparative analysis of the extant research across the three sub-domains of banking and finance, production and operations, and accounting. Findings suggest that the financial emergency in the global market had resulted in a watershed moment in trade credit research. About 69 % of the literature was found to have emerged after the global economic crisis of 2008. A network analysis grouped the trade credit articles into four major and four minor clusters. The banking and financing cluster exhibited the highest growth followed by the production and operation cluster while the perspectives of accounting are yet to gain traction. Conversely, reputation of the publishing hub, empirical studies, and the production and operational dimensions of the research positively and significantly influence citations. Alongside thorough introspection, the study also provides new areas to direct the course of future research. Emerging from the field of Banking and Finance, research in trade credit has evolved as a multi-disciplinary scientific domain with contributions from Business Management, Industrial Engineering, Production and Operations, Finance, Economics, etc. (Paul & Boden, 2008) . Prior reviews have provided partial qualitative and (or) quantitative perspectives of their respective disciplines (see Table 1 ), while the need for a holistic overview of the extant literal corpus is unaddressed. In addition, the precise factors contributing to the growth in literature in this fastevolving academic domain lack empirical support. As an example, in one of the recent reviews, Pattnaik et al. (2020) provided a comprehensive overview of the literal corpus on trade credit covered in top finance and economics journals between 1999 and February, 2019. However, the study misses out the basic multi-disciplinary nature of the research domain. Therefore, views from other important disciplines e.g., Industrial Engineering, Production and Operations etc. excluded in the former are included in this endeavor. Alternatively, while the former evaluates only 138 articles covered in Web of Science (WOS); this work analyzes 1,191 works of research available in Scopus. In addition, both the studies also differ in their analytical outfits. The primary concern of the first review is on network analysis and therefore exhibits limitations in the descriptive front. However, this endeavor is rich in both descriptive, network, and predictive contents of the multidisciplinary research domain. J o u r n a l P r e -p r o o f clustering exposes their semantic (dis)association. Further, we also explore the thematic components and introspect on the extant literature to provide some future research directions. In addition, we also identify a number of factors influencing the quantum of citations, thus indicating a growth of trade credit research. Therefore, apart from the de novo researchers, such a detailed introspection may also inform the established academics in the field about theories which require future validation and the study methods they could deploy. Moreover, this study contributes significantly to the extant research by asking the following research questions (RQs): RQ1. What is the state-of-the-art of the research front-in terms of publications, authorship and citation structure, influence, impact, activity, and productivity of its contributing authors and publishing sources-and how does it vary in the pre and post crisis era of 2008? RQ2. What is the thematic layout of the research domain? RQ3. How do the extant literature, its prolific contributors, publishing sources, and highly cited references converge intellectually? RQ4. What factors significantly contribute to the growth of the research domain? RQ5. What is the direction for actionable research in future? In the remaining sections, we summarise the research methods, discuss the study outcomes, provide key summaries, and conclude the paper. (Insert Table 1 about here) Trade credit-in form of receivables-is a financing provision by non-financing firms (García-Teruel & Martínez-Solano, 2010) with or without bank intermediation. In the context of a complex and competitive global market, credit supply is inevitable to retain B2B relations and impart business growth (Chowdhury & Lang, 1996) while financing supply chain is must for obtaining competitive advantage (Pirttilä et al., 2019) . Enhanced fluctuations in the level of industrial production backed by disruptive technologies significantly distress trade credit policies both for the upstream and downstream supply chain. The nature of the product, fluctuations in market demand and the level of hostility in the business environment further impact its demand and supply. Buyers benefit from the time value of money by increasing their demand for credit supplies while suppliers, on the other hand, register a growth in sales (Schwartz, 1974) . Simultaneously, empirical evidences assert the influential role of a number of qualitative indicators such as the national culture (El Ghoul and Zheng, 2016) , the cultural background of finance managers (Bedendo et al. 2020) , and level of social trust (Levine et al. 2018) impacting the demand and supply of trade credit. Demand for trade credit is also influenced by the level of financial market development and financing constraints. More importantly, trade credit substitutes bank credit during a crisis (Bastos & Pindado, 2013) and therefore is a viable source of finance both in the developed and developing world (McMillan & Woodruff, 1999; Afrifa & Gyapong, 2017; Li et al., 2018) . Suppliers' credit played a crucial role in the survival of SMEs during the crisis. Empirical evidence substantiates the argument that trade credit reduces the likelihood of financial distress among SMEs (McGuiness et al. 2018) . Simultaneously, it impacts the production cycles, optimal ordering quantity, level of inventory, firm performance, and industry growth (Haley & Higgins, J o u r n a l P r e -p r o o f 1973; Barth et al., 2001; Huang, 2003 Huang, , 2007 Huang & Hsu, 2008; Fisman & Love, 2003; Chung & Huang, 2003; Chung et al., 2005; Liao, 2008; Allen et al. 2019 ). In the chronological progression of the research domain, the intertwined financing and accounting perspectives of trade credit shows signs of separation. Few notable thinkers such as Brick and Fung (1984) proposed the tax theory of trade credit, hypothesising that businesses offer trade credit to obtain tax benefit. Other themes explored in this area include revenue management and budgetary participation among others. Thus, the literature analysed exhibit three broader academic domains: first, the banking and financing aspects, and second, the production and operational dimensions, and third the accounting perspectives of trade credit. In order to delineate the potential factors contributing to the popularity of trade credit literature in academia this study applies both quantitative and qualitative tools. In the field of scientometrics citations are predominantly considered to be the indicators of quantity versus that of quality (Aksnes et al. 2019 ). On the basis of citations, Hirsch (2005) proposed the "h-index" while Egghe (2006) proposed the "g-index". Both Hirsch and Egghe provide authorial performance indicators measuring the quantitative performance of authors. Drawing from such prior evidence, we examined citation as a growth factor for a research domain as every new citation is the birth of a new publication. Alternatively, it also adds to the influence and impact of the academic source cited, the specific theme cited, and contributes to the intellectual influence of its contributor(s). Given the debatable qualitative indications of citations (Aksnes et al. 2019 ), we present qualitative perspectives i.e. journal's academic reputation, an author's academic reputation, etc. Alternatively, Ball & Tunger (2006) argue that growth in publications indicates a growing research area while Acedo et al. (2006) and Finardi & Burati (2016) associate growth with authorial collaborations. Other factors include an increase in global submissions and publications in prestigious academic outlets (Merigó et al., 2019; Baker et al. 2020) , etc. Alongside the hypothetical constructs, this study also applies some of the tested factors affecting citations (growth in publications) by drawing upon Schwert's work (1993) . By combining all the theoretical perspectives, the conceptual model of our study is proposed in Figure 1 . During academic emergency or external threats to industry (environment)-established research domains grow faster. Growth of the broader academic domain is also due to the upsurge in research activities of the interrelated disciplines. In such circumstances, published articles in reputed journals positively affect growth. The growing inter-disciplinary variable mediates between the primary established academic domain and the discipline's overall growth. In other words, by drawing wisdom from the (reputed) publications and the established academic domain, the growing inter-disciplinary sub-domain(s) expand(s) the broader horizon of knowledge further. J o u r n a l P r e -p r o o f Data analysed in this study was furnished from Scopus. It is one of the largest databases (Bartol et al., 2014) of peer-reviewed works in social science (Norris & Oppenheim, 2007) , extensively accessed for quantitative analyses (Durán-Sánchez et al., 2019; Baker et al. 2020; Donthu et al. 2020) . Figure 2 summarises the study design. (Insert Figure 2 about here) To carry out the investigation, a broad search term was finalised. The term, "trade credit" OR "account* receivable*" OR "account* payable*", searched in the title, abstract or keywords enabled access to the extant literature in Scopus. Redundant documents were eliminated using subject filters. Literature confined to Business Management, Accounting, Economics, Econometrics, Finance, Social Sciences, Arts and (or) Humanities were included. Since our focus was accessing the core bibliographic records on trade credit; only those documents classified as articles, reviews, or conference proceedings were included and the rest excluded. Further, due to the dynamic nature of the research domain literature published in 2020 is omitted. Finally, a total of 1,191 documents published between 1955 and 2019 were considered for analyses. The descriptive analysis in this study was conducted manually using Microsoft (MS) Excel under the four broad categories of: 1. Publication trend. 2. Authorship pattern. 3. Citation structure. 4. The influence, impact, activity, and productivity indicators (Donthu et al. 2020; Baker et al. 2020) . Refer Appendix I for definitions of the descriptive variables. J o u r n a l P r e -p r o o f The study explores the thematic factors of the research domain using Principal Component Analysis (PCA) with Varimax rotation under Kaiser Normalisation. It was conducted with the help of the Statistical Packages for the Social Sciences (SPSS) software. The core of such an analysis is based on the co-occurrence counts of the keywords indicating themes (Callon et al. 1983; Marrone, 2020) . Ponzi (2002) applied a similar technique to explore the intellectual structure among frequently co-occurring authors. To carry out the analysis, prolific themes appearing at least five times in the shortlisted articles are identified. Using MS-Excel, the co-occurrence matrix of those themes was later processed in SPSS to obtain the Pearson's correlations. Finally, we used the correlations' matrix to explore the thematic components. When two distinct works cite one or more common documents, they exhibit intellectual similarities (Kessler, 1963) ; whereas, co-citation is the citation of two or more existing researches in a later article (Small, 1973) . The network analyses in the forms of bibliographic couplings (Kessler, 1963) and co-citations (Small, 1973) unveil the semantic clustering among the citing and cited documents, contributing authors, publishing sources, etc. (Merigó et al., 2019; Donthu et al. 2020; Baker et al. 2020) . The networks in this study are visualized using VOSviewer and Gephi software (van Eck & Waltman, 2017; van Eck & Waltman, 2010; Bastian et al., 2009) . Both the programs apply two standardized weights for visualising the networks e.g. the total number of links and the total strength of the links. The size of the nodes in a network indicates its relevance; whereas, the J o u r n a l P r e -p r o o f number and size of the interlinking lines represent the strength of the association among the nodes (van Eck & Waltman, 2017). We apply the Ordinary Least Square (OLS) regression in SPSS to explore the potential growth factors of the research domain (Dragos et al. 2014) . Drawing primarily from previous research (Schwert, 1993) , the following model is proposed: Total citations = Article length + Number of contributing authors + Authorship type (sole-authored or co-authored) + Publication year (before or after 2008) + AJG 2018 ratings + Bibliographic cluster of the article (major or minor) + Study method (primary or secondary) + Thematic components' score + error (Eq.1) The dependent variable, total citations, is defined as the total quantitative growth of the research domain. Article length-defined as the number of pages of the article. Number of contributing authors-defined as the total number of authors who contributed to the article. Thematic score-respective thematic component scores of the articles. Dummy variables include, authorship type (sole-authored or co-authored), publication year ( Figure 3 shows the yearly growth in publications, its influence (h-index), and the average annual citations of the articles published between 1955 and 2019. Figure 4 depicts the annual trend of the intelligentsia, while Figure 5 distributes the trade credit articles by its number of contributors. It also compares the authorial distribution of the articles before and after 2008. (Insert Table 2 Figure 3 depicts an exponential growth in publications since 2008. As indicated in Table 1 , about 69% (TP: 823 of 1,191) of the study articles are published after 2008. Thus, the majority of the research on trade credit followed the global economic crisis of 2008. Such a trend is not surprising as-during the collapsing phase of banking-academia largely proclaimed trade credit as the primary source of alternate finance that sustained the global economy (Giannetti et al. 2011; Chor and Manova, 2012) . Conversely, as the demand was non-decreasing post 2008, the proposition of the economic order quantity model by Teng et al. (2012) attracted further research attention (see Table 3 ). Not only did academia recognise trade credit as a major source of finance over these years, trade credit also managed to establish itself as one of the predominant factors influencing factors like economic order quantity (EOQ), economic production quantity (EPQ), the shifts in the volume of production, etc. From another perspective, an evolving research domain triggers further research attention by attracting and engaging more scholars (Ball & Tunger, 2006) . The notion is evidentially affirmed in Figure 4 . The figure depicts an increasing trend in the number of thinkers. 2,062 unique researchers have contributed to the domain between 1955 and 2019 (see Table 2 In conclusion, the protective mechanism of trade credit as an alternative source of finance during banking emergency has historically triggered academic attention between 2008 and 2019. With the pandemic onset of COVID-19 shutting down operations, we foresee a similar trend in the production and operational area of trade credit research in the near future. Table 3 presents the top articles published before and after 2008. (Insert Table 3 Interestingly, the top three highly cited works exhibit convergence in their respective philosophical outlooks. Petersen and Rajan (1997) predominantly present the banking and financing views of trade credit research while both Dechow et al. (1998) and Barth et al. (2001) navigate the broader finance and accounting dimensions. However, the model proposed in the note by Huang (2003) modified the production and operational dimensions concerning the trade J o u r n a l P r e -p r o o f credit policies of retailers. While earlier notions predominantly argued against the extension of credit period by retailers, Huang (2003) proposed that like suppliers, retailers stimulate their demand by extending the credit period to their customers. Thus, the highly cited articles, depicting the existing knowledge in the established academic domain, presumably influence their respective research sub-domains. However, a deeper investigation of the highly cited articles reveal that the accounting dimension of trade credit is dormant without any significant contribution in the post-crisis era thereby presenting scope for future research. In the subsequent discussion, we recognize some of the most prolific and influential thinkers in the broader domain. Table 4 lists some of the most prolific authors who have contributed at least five works of research between 1955 and 2019. (Insert Table 4 (Insert Table 5 Table 6 enlists the prominent themes of the extant literature on trade credit which have been discussed in at least 10 articles. (Insert Table 6 Table 7 presents the communalities of the 68 thematic items. Table 8 shows the loading of the thematic items to their respective components and also presents the reliability of the thematic scale. (Insert Table 7 about here) (Insert Table 8 (Kessler, 1963) while Small (1973) argued that frequent co-citations of published articles in the subsequent research evidentially confirms intellectual association. Unfortunately, the argument of Small (1973) may suffer a time lag effect as more recent publications require time to influence academic evidence in the form of citations (Marrone, 2020) . Since our study incorporates articles till 2019, we applied bibliometric coupling analysis on the trade credit articles, authors, and publishing sources. However, to expose the prior seminal ideas, we applied co-citation analysis on the cited references as explained by Small (1973) . Table 9 presents the descriptive analyses of the bibliographic clusters, Figure 8 reveals the publication trend of the clusters in the pre and post crisis era, while Figure 9 shows the kind of studies that prevailed within the respective bibliographic clusters. (Insert Table 9 Further, as indicated in Figure 9 , most of the articles are empirical investigations while the cluster contributes a smaller number of qualitative researches such as conceptual papers, reviews etc., thereby suggesting few methodological gaps for the aspiring contributors to fulfil. Of note is that some of the influential themes of the cluster include terms such as firm value, corporate social responsibility, earnings and cash flows, prediction of future cash flows, etc. Some of its recent and original publications draw upon transactions cost theory; for eg. The third cluster is the most competitive cluster of the research front occupying the topmost rank in the majority of the indicators reported in Table 9 (TP: 415 the supplier-retailer's relation mediate the above proposition. We argue that apart from establishing the credit quality of the new buyers, the incremental increase of credit supply with age may naturally eliminate the risk of free-riding. Cluster 5 Most of the latest articles published in the cluster work in the area of green supply chains, operational management, optimal ordering quantity, optimal wholesale price, optimal carbon J o u r n a l P r e -p r o o f emissions, etc. As an example, the amalgamative supply chain operations model of Dash (2019) addressing the concern of optimal carbon emissions (OCE), optimal ordering quantity (OOQ) of a capital-constraint retailer, and the optimal wholesale price (OWP) for a manufacturer operating in a viable trade credit financing and bank financing market environment proposed and validated that lower levels of carbon emissions fosters win-win outcomes. Future empirical validations of such models can sensitise controlled carbon emissive behaviour as it positively impacts profitability. It can be concluded that the bibliographic coupling analysis affirms three major subdomains of trade credit (banking and financing, accounting, and production and operations) gradually expanding to eight specialized sub-domains. The following section visualizes the intellectual epicentres of trade credit research, and the network among the most prolific authors and contributing sources. Schwartz (1974) . Interestingly, excluding Goyal (1985) , Aggarwal and Jaggi (1995) , and Teng (2002) all the remaining articles are closely knitted. It suggests that the operational dimension of trade credit stand out from the remaining perspectives. Interestingly, Figure 11 also presents three broad groups of intellectuals. However, X. Chen and D. Yazdanfar stand out in their referencing pattern exhibiting similarities with N. H. Shah and L. -Y. Ouyang, respectively. In Figure 12 , the majority of the journals present the financial perspectives of trade credit In the subsequent section we report the outcome of the regression analysis revealing some key variables influencing the total citations of the discipline over the years. J o u r n a l P r e -p r o o f Table 10 presents the description of the studied variables, Table 11 presents the correlation matrix of the studied variables while Table 12 presents the regression coefficients of the variants. (Insert Table 10 about here) (Insert Table 11 about here) (Insert Table 12 Although the directions for future research are already presented during the analysis of the bibliographic networks, we summarise some of the key aspects here. While analysing the gaps in research methods, we suggest future research to be more qualitative in nature. Researchers should consider providing more conceptual and theoretical models, specialized pathways, survey-based studies etc. in the emerging clusters to fortify the domains. Simultaneously, we call for more studies with empirical insights from emerging economies that would educate global academia which has largely observed this phenomenon Simultaneously , Paul et. al. (2018) presented receivables as an alternative investment. However, the social nature of trade credit is unexplored. Given its importance, we argue that trade credit is not only commercial, it also has social implications, especially when the relation is between the large-scale lender to the micro, small, and medium enterprises (MSMEs). Further, drawing from the model of Dash (2019), future research could also explore the impact of green trade credit on firm's accounting, market, and social performances. Conversely the behavioral dimensions in the research front is unexplored. With regard to the application of theories in this area, we suggest that there are opportunities to carry out researches using theories such as the prospect theory and dynamic capability theory. Prospect theory was originally developed by economists Kahneman and Tversky (1979) . It constitutes one of the first economic theories formulated using experimental methods. Prospect describes how individuals asymmetrically assess their loss and gain perspectives relative to their specific situation. They found that individuals are risk-averse when facing gains but risk-lovers when facing losses. Accordingly, the prospect theory describes the actual behavior of people. In the original formulation of the theory, the term prospect referred to the predictable results of a lottery. However, the prospect theory can also be applied to the prediction of other forms of behaviors and decisions in areas such as trade credit. Similarly, tenets of dynamic capability framework (Teece, 2007) can be applied in trade credit research to analyze how the firm capabilities and trade credit influence firm performance. The state-of-the-art in trade credit literature indicates an evolving growth trend. A growing discipline attracts more researchers from multiple disciplines resulting in synergetic (1), 301-309. https://doi.org/10.1111 /j.1540 -6261.1990 .tb05095.x Chung, K.-J., Goyal, S. K., & Huang, Y.-F. (2005 . The optimal inventory policies under permissible delay in payments depending on the ordering quantity. International Journal of Production Economics, 95 (2) Financial and economic perspectives Notes: This table presents some of the former reviews on trade credit. It includes the author(s) of the study, type of study (TOS), the study method, study period, number of articles analysed (NA) and the primary focus of the study. ND stands for not defined period/articles. This table presents the publication Here, IIAP = influence, impact, activity, and productivity; TP = total publications; B08 = number of publications before 2008; A08 = number of publications after 2008; NCA = number of contributing authors; CI = collaboration index; SA = number of sole-authored articles; CA = number of co-authored articles; PCP = proportion of cited publications; C/CA = citations per contributing author; CT1 = first citation threshold i.e. between 1 and 99 cites; CT2 = second citation threshold i.e. between 100 and 499 cites; h = h-index; g = g-index; NAY = number of active years; and PAY = productivity per active year. Here, IIAP = influence, impact, activity, and productivity; TP = total publications; NCA = number of contributing authors of those publications; CI = collaboration index; SA = sole-authored articles; CA = co-authored articles; PCP = proportion of cited publication; TC = total citations; C/CP = citations per cited publication; C/CA = citations per contributing author; CT1 = first citation threshold i.e. between 1 and 99 citations; CT2 = second citation threshold i.e. between 100 and 499 citations; CT3 = third citation threshold i.e. above 500 citations; h = h-index; g = g-index; NAY = number of active years; and PAY = publications per active year; and NA = not available. Here, SD = standard deviation, N = number of cases, and NA = not applicable. The dummies include: authorship type of the trade credit articles i.e. sole-authored or co-authored; publication year of the articles i.e. before or after 2008; AJG 2018 ratings of the publishing sources of the trade credit articles such as 4*, 4, 3, 2, or 1; bibliographic clustering of the trade credit articles i.e. major or minor cluster; and research type of the trade credit articles i.e. primary (empirical) or secondary (review, conceptual, model building, etc.). Apart from reporting the standardized coefficients (SC) of the independent variables influencing the dependent (total citations), the table also presents the collinearity statistics (CS) such as tolerance (T) and the variance inflation factors (VIF) of the regressors. Of note, the R 2 of the model is 0.34 with an adjusted R 2 value of 0.33. The regression is significant at 99% confidence interval (p-value ≤ 0.01). Here, T = tolerance; and VIF = variance inflation factor. Citations, citation indicators, and research quality: An overview of basic concepts and theories Understanding informal financing Twenty-five years of the Journal of Corporate Finance: A scientometric analysis Bibliometric analysis -A new business area for information professionals in libraries? Accruals and the prediction of future cash flows Assessment of research fields in Scopus and Web of Science in the view of national research evaluation in Slovenia Gephi: An open source software for exploring and manipulating networks Trade credit during a financial crisis: A panel data analysis Fuzzy decision making: A bibliometric-based review Cultural preferences and firm financing choices Taxes and the theory of trade debt From translations to problematic networks: An introduction to co-word analysis Turnaround in small firms: An assessment of efficiency strategies Off the Cliff and Back? Credit Conditions and International Trade during the Global Financial Crisis Determinants of trade credit: A comparative study of European SMEs What you sell is what you lend? Explaining trade credit contracts STEM education: A bibliometric overview A bibliometric study of reference literature in the sciences and social sciences1 Economic order quantity under conditions of permissible delay in payments Partial least squares: the better approach to structural equation modeling? Long Range Planning Inventory policy and trade credit financing Science studies: An advanced introduction An index to quantify an individual's scientific research output Optimal retailer's ordering policies in the EOQ model under trade credit financing Optimal retailer's replenishment decisions in the EPQ model under two levels of trade credit policy An EOQ model under retailer partial trade credit policy in supply chain Prospect theory: An analysis of decision under risk Analysing entrepreneurship education: A bibliometric survey pattern Bibliographic coupling between scientific papers Corporate resilience to banking crises: The roles of trust and trade credit Legal System and Trade Credit: Evidence from Emerging Economies. Emerging Markets Finance and Trade An EOQ model with noninstantaneous receipt and exponentially deteriorating items under two-level trade credit Application of entity linking to identify research fronts and trends European trade credit use and SME survival Interfirm relationships and informal credit in Vietnam Research in production and operations management: A university-based bibliometric analysis Assessing the usefulness of bibliometric indicators for the humanities and the social and behavioural sciences: A comparative study Comparing alternatives to the Web of Science for coverage of the social sciences' literature Qualitative Research in Financial Markets, ahead-of-print(ahead-of-print The secret life of UK trade credit supply: Setting a new research agenda Trade credit: Theories and evidence Working capital management in the Russian automotive industry supply chain Scholarly influence in the field of management: A bibliometric analysis of the determinants of university and author impact in the management literature in the past quarter century The intellectual structure and interdisciplinary breadth of Knowledge Management: A bibliometric study of its early stage of development Statistical bibliography or bibliometrics An economic model of trade credit Co-citation in the scientific literature: A new measure of the relationship between two documents Explicating dynamic capabilities: the nature and microfoundations of (sustainable) enterprise performance. Strategic management journal On the economic order quantity under conditions of permissible delay in payments Economic order quantity model with trade credit financing for non-decreasing demand Citation analysis of Ted Nelson's works and his influence on hypertext concept Software survey: VOSviewer, a computer program for bibliometric mapping VOSviewer Manual Using Payment Behaviour Data for Credit Risk Modelling Supply chain finance: A systematic literature review and bibliometric analysis financial intermediary development, and industry growth" Fisman R., Love I. bank credit: Evidence from recent financial crises Sarria-Allende V. In-kind finance: A theory of trade credit Bank discrimination in transition economies: Ideology, information, or incentives Are accruals during initial public offerings opportunistic An EOQ model with noninstantaneous receipt and exponentially deteriorating items under two-level trade credit" Liao J.-J. multi-delay-in-payments under single-setup-multiple-delivery policy in a global sustainable supply chain chain finance: A systematic literature review and bibliometric analysis international trade during the 2008-09 crisis: In search of the smoking gun Ranking (R) of the articles are based on their respective average citations per year (CPY). Here, TC = total citations, and C/CA = citations per contributing author Notes: This table presents the Pearson's correlation among the potential variables influencing the citations of trade credit articles 15 = type of the trade credit research (empirical or secondary); 16 = empirical research Defined as the sum of total publications B08Defined as the number of publications before 2008 A08Defined as the number of publications after 2008 Authorship pattern NCA Number of authors contributing the research article(s). Annual increment of authors added to the research domain. Ratio between the number of contributing authors to total publications less the number of total publications ( − 1). Number of articles contributed by a single author. Number of articles contributed by multiple authors. The number of articles cited at least once in Scopus. Ratio between the number of cited publications to the total number of publications. Sum of the citations accredited to an article, an author, a journal, a cluster, etc. C/P Average citations per publication. Average citations per cited publication. Average citations per contributing author. Citations between 1 and 99 times. Citations between 100 and 499 times. CT3 500 citations and above. Influence, impact, productivity, and activity h h number of publications cited at least h times. gSum of g number of highly cited publications cited at least g 2 times. Number of years an article or a theme on trade credit was published or the number of years an academic source &/or a cluster published on trade credit. Number of publications in each of the active years.